Papers to Appear in Subsequent Issues

Functional Data Analysis by Matrix Completion Marie-Hélène Descary and Victor Michael Panaretos
Computation of Maximum Likelihood Estimates in Cyclic Structural Equation Models Mathias Drton, Christopher Fox, and Y. Samuel Wang
Exact recovery in the Ising blockmodel Quentin Berthet, Philippe Rigollet, and Piyush Srivastava
Fréchet regression for random objects with Euclidean Predictors Alexander Petersen and Hans-Georg Müller
Divide and Conquer in Non-Standard Problems and the Super-Efficiency Phenomenon Moulinath Banerjee, Cecile Durot, and Bodhisattva Sen
Rank Verification for Exponential Families Kenneth Hung and William Fithian
Sub-Gaussian estimators of the mean of a random vector Gábor Lugosi and Shahar Mendelson
Combinatorial Inference for Graphical Models Matey Neykov, Junwei Lu, and Han Liu
Estimation and Prediction using generalized Wendland Covariance Functions under fixed domain asymptotics Moreno Bevilacqua, Tarik Faouzi, Reinhard Furrer, and Emilio Porcu
Chebyshev polynomials, moment matching, and optimal estimation of the unseen Yihong Wu and Pengkun Yang
Maximuim likelihood estimation in Gaussian models under total positivity Steffen Lilholt Lauritzen, Caroline Uhler, and Piotr Zwiernik
Distribution theory for hierarchical processes Federico Camerlenghi, Antonio Lijoi, Peter Orbanz, and Igor Pruenster
Adaptive Estimation of the Sparsity in the Gaussian Vector Model Alexandra Carpentier and Nicolas Verzelen
Partial Least Squares Prediction in High-Dimensional Regression R. Dennis Cook and Liliana Forzani
Signal Aliasing in Gaussian Random Fields for Experiments with Qualitative Factors Ming-Chung Chang, Shao-Wei Cheng, and Ching-Shui Cheng
Approximate Optimal Designs for Multivariate Polynomial Regression Yohann De Castro, Fabrice Gamboa, Didier Henrion, Roxana Hess, and Jean-Bernard Lasserre
Efficient Estimation of Integrated Volatility Functionals via Multiscale Jackknife Jia Li, Yunxiao Liu, and Dacheng Xiu
Non-Asymptotic Rates for Manifold, Tangent Space, and Curvature Estimation Clément Levrard and Eddie Aamari
Nonparametric testing for multiple survival functions with non-inferiority margins Hsin-wen Chang and Ian W. McKeague
Estimation in the convolution structure density model. Part I: oracle inequalities Oleg Lepski and Thomas Willer
Efficient multivariate entropy estimation via k-nearest neighbour distances Thomas Benjamin Berrett, Richard John Samworth, and Ming Yuan
Posterior Graph Selection and Estimation Consistency for High-Dimensional Bayesian Dag Models Malay Ghosh, Kshitij Khare, and Xuan Cao
Locally adaptive confidence bands Tim Patschkowski and Angelika Rohde
Asymptotic Distribution-Free Change-Point Detection for Multivariate and non-Euclidean Data Lynna Chu and Hao Chen
Statistics on the (Compact) Stiefel Manifold: Theory and Applications Rudrasis Chakraborty and Baba Vemuri
Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes Juan A. Cuesta-Albertos, Eduardo García-Portugués, Manuel Febrero-Bande, and Wenceslao González-Manteiga
Cross: Efficient Low-rank Tensor Completion Anru Zhang
Convolved Subsampling Estimation with Applications to Block Bootstrap Johannes Tewes, Daniel J. Nordman, and Dimitris N. Politis
Feature elimination in kernel machines in moderately high dimensions Sayan Dasgupta, Yair Goldberg, and Michael R Kosorok
Testing in High-Dimensional Spiked Models Iain M Johnstone and Alexei Onatski
Covariate balancing propensity score by tailored loss functions Qingyuan Zhao
High-dimensional covariance matrices in elliptical distributions with application to spherical test Jiang Hu, Weiming Li, Zhi Liu, and Wang Zhou
A critical threshold for design effects in network sampling Karl Rohe
The geometry of hypothesis testing over convex cones: Generalized likelihood ratio tests and minimax radii Yuting Wei
Permutation p-value approximation via generalized Stolarsky invariance Art B Owen
Nonparametric Implied Levy Densities Likuan Qin and Viktor Todorov
Canonical correlation coefficients of high-dimensional Gaussian vectors: finite rank case Zhigang Bao, Jiang Hu, Guangming Pan, and Wang Zhou
Uniform Projection Designs Fasheng Sun, Yaping Wang, and Hongquan Xu
On model selection from a finite family of possibly misspecified time series models Hsiang-Ling Hsu, Ching-Kang Ing, and Howell Tong
Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap Miles Lopes
Efficient Nonparametric Bayesian Inference for X-ray transforms Francois Monard, Richard Nickl, and Gabriel P Paternain
Generalized Random Forests Susan Athey, Julie Tibshirani, and Stefan Wager
Approximating faces of marginal polytopes in discrete hierarchical models Nanwei Wang, Johannes Rauh, and Helene Massam
CHIME: Clustering of High-Dimensional Gaussian Mixtures with EM Algorithm and Its Optimality Tony Cai, Jing Ma, and Linjun Zhang
Bayesian fractional posteriors Anirban Bhattacharya, Debdeep Pati, and Yun Yang
Distributed Estimation of Principal Eigenspaces Jianqing Fan, Dong Wang, Kaizheng Wang, and Ziwei Zhu
Exponential ergodicity of the Bouncy Particle Sampler George Deligiannidis, Alexandre Bouchard-Cote, and Arnaud Doucet
The Zig-Zag process and Super-Efficient Sampling for Bayesian Analysis of Big Data Joris Bierkens, Paul Fearnhead, and Gareth O. Roberts
Estimation of Large Covariance and Precision Matrices from Temporally Dependent Observations Hai Shu and Bin Nan
Bootstrap tuning in ordered model selection Vladimir Spokoiny and Niklas Willrich
Sequential change-point detection based on nearest neighbors Hao Chen
Prediction when fitting simple models to high-dimensional data Lukas Steinberger and Hannes Leeb
Two-Sample and ANOVA Tests for High Dimensional Means Song X Chen, Jun Li, and Pingshou Zhong
Valid confidence intervals for post-model-selection predictors François Bachoc, Hannes Leeb, and Benedikt Poetscher
A robust and efficient approach to causal inference based on sparse sufficient dimension reduction Shujie Ma, Liping Zhu, Zhiwei Zhang, Chih-Ling Tsai, and Raymond Carroll
A Classification Criterion for Definitive Screening Designs Eric Schoen, Pieter Eendebak, and Peter Goos
The Maximum Likelihood Threshold of a Path Diagram Mathias Drton, Christopher Fox, Andreas Käufl, and Guillaume Pouliot
Convex Regularization for High-dimensional Multi-response Tensor Regression Garvesh Raskutti, Ming Yuan, and Han Chen
Maximum likelihood estimation in transformed linear regression with non-normal errors Xingwei Tong, Fuqing Gao, Kani Chen, Dingjiao Cai, and Jianguo Sun
Large Sample Theory for Merged Data from Multiple Sources Takumi Saegusa
Khinchine’s theorem and Edgeworth approximations for weighted sums Sergey G. Bobkov
Hypothesis Testing for Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates Sivaraman Balakrishnan and Larry Wasserman
Distributed Inference for Quantile Regression Processes Stanislav Volgushev, Shih-Kang Chao, and Guang Cheng
Gaussian approximation of maxima of Wiener functionals and its application to high-frequency data Yuta Koike
Causal Dantzig: fast inference in linear structural equation models with hidden variables under additive interventions Dominik Rothenhäusler, Peter Bühlmann, and Nicolai Meinshausen
Non-penalized variable selection in high-dimensional linear model settings via generalized fiducial inference Jonathan Paul Williams and Jan Hannig
The BLUE in regression models with correlated errors Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky
Adaptive-to-model checking for regressions with diverging number of predictors Falong Tan and Lixing Zhu
Super-resolution estimation of cyclic arrival rates Ningyuan Chen, Donald K.K. Lee, and Sahand N. Negahban
Sequential Multiple Testing with Generalized Error Control: An Asymptotic Optimality Theory Yanglei Song and Georgios Fellouris
Nonparametric Screening under Conditional Strictly Convex Loss for Ultrahigh Dimensional Sparse Data Xu Han
Local stationarity and time-inhomogeneous Markov chains Lionel Truquet
High-dimensional change-point detection with sparse alternatives Farida Enikeeva and Zaid Harchaoui
Perturbation Bootstrap in Adaptive Lasso Debraj Das, Karl Gregory, and Soumendra Nath Lahiri
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions Guillaume Lecue, Pierre Alquier, and Vincent Cottet
Cross validation for locally stationary processes Stefan Richter and Rainer Dahlhaus
Generalized Cluster Trees and Singular Measures Yen-Chi Chen
Spectral Method and Regularized MLE are Both Optimal for Top-K Ranking Yuxin Chen, Jianqing Fan, Cong Ma, and Kaizheng Wang
Negative association, ordering and convergence of resampling methods Mathieu Gerber, Nicolas Chopin, and Nick Whiteley
On deep learning as a remedy for the curse of dimensionality in nonparametric regression Benedikt Bauer and Michael Kohler
Convergence rates of least squares regression estimators with heavy tailed errors Qiyang Han and Jon A. Wellner
Convergence complexity analysis of Albert and Chib’s algorithm for Bayesian probit regression Qian Qin and James P. Hobert
On Testing Conditional Qualitative Treatment Effects Chengchun Shi, Wenbin Lu, and Rui Song
Dynamic network models and graphon estimation Marianna Pensky
The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics Joshua Cape, Minh Tang, and Carey E. Priebe
Isotonic regression in general dimensions Qiyang Han, Tengyao Wang, Sabyasachi Chatterjee, and Richard John Samworth
Property Testing in High Dimensional Ising Models Matey Neykov and Han Liu
A knockoff filter for high-dimensional selective inference Rina Foygel Barber and Emmanuel J Candes
Semi-supervised Inference: General Theory and Estimation of Means Anru Zhang, Lawrence D. Brown, and T. Tony Cai
Penalized Estimation in Additive Regression with High-Dimensional Data Zhiqiang Tan and Cun-Hui Zhang
Semiparametrically Optimal Hybrid Rank Tests for Unit Roots Bo Zhou, Ramon van den Akker, and Bas Werker
Sorted Concave Penalized Regression Long Feng and Cun-Hui Zhang
The middle-scale asymptotics of Wishart matrices Didier Chételat and Martin T. Wells
Linear hypothesis testing for high dimensional generalized linear models Chengchun Shi, Rui Song, Zhao Chen, and Runze Li
An Operator Theoretic Approach to Nonparametric Mixture Models Robert Anton Vandermeulen and Clayton Scott
Phase transition in the spiked random tensor with Rademacher prior Wei-Kuo Chen
Distance multivariance: New dependence measures for random vectors Björn Böttcher, Martin Keller-Ressel, and Rene L. Schilling
A Unified Treatment of Multiple Testing with Prior Knowledge using the p-filter Aaditya K. Ramdas, Rina F. Barber, Martin J. Wainwright, and Michael I. Jordan
Exact Lower Bounds for the Agnostic Probably-Approximately-Correct (PAC) Machine Learning Model Iosif Pinelis and Aryeh Kontorovich
Eigenvalue distributions of variance components estimators in high-dimensional random effects models Zhou Fan and Iain Johnstone
Global Test Statistics for High Dimensional  Correlation Matrices S. R. Zheng, Guanghui Cheng, Jianhua Guo, and Hongtu Zhu
Projected Spline Estimation of the Nonparametric Function in High-dimensional Partially Linear Models for Massive Data Heng Lian, Kaifeng Zhao, and Shaogao Lv
Inference for the mode of a log-concave density Charles R. Doss and Jon A. Wellner